Tensor networks (TNs) have undergone rapid development in the last two decades, gaining tremendous success in quantum many-body physics, quantum information sciences, statistical physics, and so on. Tensor network algorithms based on matrix product states (MPS)[1]}, [2]}, projected entangled pair states (PEPS)[3]}, [4]}, and variational renormalization group methods are very efficient in simulating a large class of quantum many-body systems. The tensor network structure can encode the combinatorial optimization problem with local constraints, providing an idea of utilizing the tensor network to solve combinatorial optimization problems.
